Analysis of viral load in different specimen types and serum antibody levels of COVID-19 patients.

BACKGROUND: COVID-19 has caused a global pandemic and the death toll is increasing. However, there is no definitive information regarding the type of clinical specimens that is the best for SARS-CoV-2 detection, the antibody levels in patients with different duration of disease, and the relationship between antibody level and viral load. METHODS: Nasopharyngeal swabs, anal swabs, saliva, blood, and urine specimens were collected from patients with a course of disease ranging from 7 to 69 days. Viral load in different specimen types was measured using droplet digital PCR (ddPCR). Meanwhile, anti-nucleocapsid protein (anti-N) IgM and IgG antibodies and anti-spike protein receptor-binding domain (anti-S-RBD) IgG antibody in all serum samples were tested using ELISA. RESULTS: The positive detection rate in nasopharyngeal swab was the highest (54.05%), followed by anal swab (24.32%), and the positive detection rate in saliva, blood, and urine was 16.22%, 10.81%, and 5.41%, respectively. However, some patients with negative nasopharyngeal swabs had other specimens tested positive. There was no significant correlation between antibody level and days after symptoms onset or viral load. CONCLUSIONS: Other specimens could be positive in patients with negative nasopharyngeal swabs, suggesting that for patients in the recovery period, specimens other than nasopharyngeal swabs should also be tested to avoid false negative results, and anal swabs are recommended. The antibody level had no correlation with days after symptoms onset or the viral load of nasopharyngeal swabs, suggesting that the antibody level may also be affected by other factors.

Evaluation of the clinical performance of single-, dual-, and triple-target SARS-CoV-2 RT-qPCR methods.

BACKGROUND: The coronavirus disease 2019 (COVID-19) has become a pandemic. Reverse transcription quantitative PCR (RT-qPCR) has played a vital role in the diagnosis of COVID-19, but the rates of false negatives is not ideal in dealing with this highly infectious virus. It is thus necessary to systematically evaluate the clinical performance of the single-, dual-, triple-target detection kits to guide the clinical diagnosis of this disease. METHODS: A series of reference materials calibrated by droplet digital PCR (ddPCR) and 57 clinical samples were used to evaluate the clinical performance of six single-, dual-, triple-target SARS-CoV-2 nucleic acid detection kits based on RT-qPCR. RESULTS: The dual-target kits, kit B and kit C had the highest and the lowest detection sensitivity, which was 125 copies/mL and 4000 copies/mL, respectively. Among the 57 clinical samples from patients with COVID-19, 47 were tested positive by the kit B, while 35, 29, 28, 30, and 29 were found positive by the kits A, C, D, E, and F, respectively. The number of targets in a detection kit is not a key factor affecting sensitivity, while the amount of sample loading may influence the performance of a detection kit. CONCLUSIONS: This study provides a guide when choosing or developing a nucleic acid detection kit for the diagnosis of COVID-19. Also, the absolute-quantification feature and high-sensitivity performance of ddPCR, suggesting that it can be used to review clinically suspected samples.

Comparison of qualitative and quantitative analyses of COVID-19 clinical samples.

BACKGROUND: Qualitative and quantitative detection of nucleic acids of SARS-CoV-2, the pathogen that causes coronavirus disease 2019 (COVID-19), plays a significant role in COVID-19 diagnosis, surveillance, prevention, and control. METHODS: A total of 117 samples from 30 patients with confirmed COVID-19 and 61 patients without COVID-19 were collected. Reverse transcriptase quantitative PCR (RT-qPCR) and droplet digital PCR (ddPCR) were used for qualitative and quantitative analyses of these samples to evaluate the diagnostic performance and applicability of the two methods. RESULTS: The positive detection rates of RT-qPCR and ddPCR were 93.3% and 100%, respectively. Among the 117 samples, 6 samples were tested single-gene positive by RT-qPCR but positive by ddPCR, and 3 samples were tested negative by RT-qPCR but positive by ddPCR. The viral load of samples with inconsistent results were relatively low (3.1-20.5 copies/test). There were 17 samples (37%) with a viral load below 20 copies/test among the 46 positive samples, and only 9 of them were successfully detected by RT-qPCR. A severe patient was dynamically monitored. All 6 samples from this patient were tested negative by RT-qPCR, but 4 samples were tested positive by ddPCR with a low viral load. CONCLUSION: Qualitative analysis of COVID-19 samples can meet the needs of clinical screening and diagnosis, while quantitative analysis provides more information to the research community. Although both ddPCR and RT-qPCR can provide qualitative and quantitative results, ddPCR showed higher sensitivity and lower limit of detection than RT-qPCR, and it does not rely on the standard curve to quantify viral load. Therefore, ddPCR offers greater advantages than RT-qPCR.